When combined with advanced software, the computer becomes a powerful instrument for the study of biomolecular complexes and living cells, providing researchers with graphical views and quantitative information at a level of ?delity and accuracy limited only by the quality of available structural information. State-of-the-art biomolecular and cellular simulations are demanding not only in terms of computations required for simulation, but also with respect to the e?ort and computations required in building accurate models, preparing simulations, and analyzing results. The size of structurally resolved biomolecular complexes continues to grow, threatening to overwhelm existing software tools unless they are adapted to further exploit parallel computing technologies for key modeling, analysis, and visualization tools. Simulations must incorporate information from multiple experimental imaging modalities (e.g. X-ray crystallography, cryo-EM, cryo-ET, NMR) to enhance simulation accuracy and properly reproduce conditions present in vivo. It is therefore critical that next-generation tools for model building, simulation preparation, analysis, and visualization support multi-modal simulation approaches, and interoperate with a wide variety of research tools. The complexity involved in managing numerous and diverse simulation inputs and methods poses a signi?cant challenge for reproducibility, requiring research tools to better support the automation, recording, and replay of complex simulation work?ows both by the investigator using the software and by others. The activities described in this TRD are aligned with these overarching themes, aiming to provide the research community with new tools and software features that address challenges that arise in modeling, simulating, and analyzing ever larger macromolecular and cellular complexes, incorporation of multi-modal structure data, and interoperation with a broad range of other research software. The computational and visualization challenges involved in these aims will be addressed through algorithmic innovations that leverage ?ne-grained parallel computing approaches on multi-core CPUs and GPUs, and larger scale parallel computing on clouds, clusters, and supercomputers. The data size challenges that are expected to become more pervasive in the coming years will be met through the use of advanced non-volatile memory systems, new ?le formats and compressed data structures with increasing emphasis on parallel ?lesystems. The use of high-quality video streaming will permit one to perform modeling calculations at computer centers or advanced laboratories and avoid routine transfer of large data to allow researchers to carry out their work anywhere on video-stream linked devices like laptops and will facilitate remote collaboration among investigators.